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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Contextually aware roadside radiation measurement testbed

Here we demonstrate a contextually aware multimodal roadside radiation measurement detection testbed for traffic monitoring applications in nuclear nonproliferation. Many variables in traffic such as vehicle or cargo size, mass, speed, shape, and distance of closest approach can have significant impacts on the radiation measured from a vehicle-transported radiation source. These factors can lead to uncertainties in the analysis of the radiation source, especially for lower-strength radiation sources of interest. Our testbed, known as the Multimodal Measurement System (MMS) uses non-radiation sensors including magnetometers, geophones, radiofrequency receivers, cameras, and LiDAR to extract contextual information about vehicles passing by the system. These contextual data can then be fused with data from radiation measurements to increase the system’s sensitivity and accuracy in nuclear threat detection applications. This work describes the instrumentation of the MMS and its data acquisition pipeline. Furthermore, we describe the pre-analysis performed on the raw multimodal data streams for data fusion, and the high-level machine learning analyses for detection and characterization. The variety of sensors within the MMS provides a valuable testbed that can be used to identify the combinations of contextual sensors that provide the greatest improvements to radiation source detection and characterization within the restrictions for various proliferation detection applications. The MMS is also modular so that additional combinations of sensors can be explored in the future.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Issue Summary of INL Phase IV Transient Results for IAEA CRP on HTGR UAM Benchmark

This report details the Parallel and Highly Innovative Simulation for Idaho National Laboratory (INL) Code System (PHISICS)/Reactor Excursions and Leak Analysis Program (RELAP5)-3D results obtained for the transient core exercises defined for Phase IV of the International Atomic Energy Agency (IAEA) Coordinated Research Project (CRP) on high-temperature gas cooled reactor (HTGR) uncertainty analysis in modeling (UAM). The Phase III models and results are linked to the earlier Standardized Computer Analyses for Licensing Evaluation (SCALE)/Sampler/New ESC-based Weighting Transport (NEWT) data generated for the lattice physics (lattice) stage Phase I of the CRP. The focus of this report is the Uncertainty/Sensitivity Assessment (U/SA) of the prismatic modular high-temperature gas cooled reactor (MHTGR)-350 design, and specifically for Exercises IV-1 and IV-2 of the benchmark: the Control Rod Withdrawal (CRW) and Pressurised Loss of Cooling (PLOFC) events. The statistical U/SA methodology is implemented and demonstrated using the RAVEN code, based on perturbed cross-section libraries obtained from the SCALE/Sampler sequence. Uncertainties in nuclear data (cross-sections and the average number of neutrons produced per fission, 235U[¯v ]) lead to standard deviations (uncertainties of one s) of approximately 0.5% in the core eigenvalues of the MHTGR-350 and core models. For the coupled neutronics/thermal fluid model, local power density uncertainties up to 3.6% were observed in the colder regions of the core, while the local maximum fuel temperature uncertainties reached 1.5% for the models that included thermal fluid uncertainties. The addition of thermal fluid uncertainties dominated the impacts of nuclear data uncertainties in all cases. The main contributors to uncertainties in the power density and fuel temperatures during the transients were uncertainties in the reactor operating conditions (total power, inlet mass flow rate and inlet gas temperature). Variations in the bypass flows did not have significant impact on any of the output variables. For the nuclear data uncertainties it was found that the 235U(¯v ) / 235U(¯v ) covariance produced the largest sensitivities in terms of its impact on the eigenvalue and peak reactor power. It was also observed that the impact of any nuclear data uncertainties on the maximum fuel temperature was much less significant that the impact on eigenvalue and power. Another important finding was that although the use of eight or more energy groups is recommended for best-estimate HTGR simulation, two-group models produced acceptable uncertainty and sensitivity results for most FOMs. Since the statistical U/SA methodology is computationally expensive, and most transient solver requirements will scale directly with the number of energy groups, two energy groups could be used by HTGR developers during the early stages of design when larger uncertainty margins can be tolerated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Measurements of nematic susceptibility with phase sensitive nuclear magnetic resonance in pulsed strain fields

Here, we present nuclear magnetic resonance data in BaFe 2 As 2 in the presence of pulsed strain fields that are interleaved in time with the radio frequency excitation pulses. In this approach, the preceding nuclear magnetization acquires a phase shift that is proportional to the strain and pulse time. The sensitivity of this approach is limited by the homogeneous decoherence time, T 2 , rather than the inhomogeneous linewidth. We measure the nematic susceptibility as a function of temperature and demonstrate a three orders of magnitude improvement in sensitivity. This approach will enable studies of the strain response in a broad range of materials that previously were inaccessible due to inhomogeneous broadening.

36 MATERIALS SCIENCE↗
DOE OSTI2022

CERBERUS: CED-2 Final Design Report

The goal of the Critical Experiment Reflected By copper to bEtteR Understand Scattering [CERBERUS] is to design a critical experiment that maximizes sensitivities to copper (Cu) reactions, particularly in the intermediate energy region (0.625 eV – 100 keV) as well as the 100 – 600 keV energy region. Despite the number of experiments evaluated in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook1 , there is still a lack of benchmarks sensitive to neutrons in the intermediate energy region. The ZEUS series was designed specifically to provide data in the intermediate energy range. The ZEUS series used Cu reflectors to allow for the construction of an intermediate energy system that could be constructed within a reasonable size. While the reflection provided by Cu reduces the size of the system, it creates a system that is very sensitive to the angular scattering in Cu. A neutron scattering off Cu at some angles reflects back into to the system, while at other angles, it is lost entirely. Of the ICSBEP benchmarks sensitive to neutrons in the intermediate energy region, very few are also sensitive to Cu in that region. Improving Cu nuclear data is important outside of the ZEUS series, because it is present in many bronze and aluminum alloys, which are used in various nuclear operations such as motors, wires, and some containers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

From sequence to protein structure and conformational dynamics with artificial intelligence/machine learning

The 2024 Nobel Prize in Chemistry was awarded in part for de novo protein structure prediction using AlphaFold2, an artificial intelligence/machine learning (AI/ML) model trained on vast amounts of sequence and three-dimensional structure data. AlphaFold2 and related models, including RoseTTAFold and ESMFold, employ specialized neural network architectures driven by attention mechanisms to infer relationships between sequence and structure. At a fundamental level, these AI/ML models operate on the long-standing hypothesis that the structure of a protein is determined by its amino acid sequence. More recently, AlphaFold2 has been adapted for the prediction of multiple protein conformations by subsampling multiple sequence alignments. Herein, we provide an overview of the deterministic relationship between sequence and structure, which was hypothesized over half a century ago with profound implications for the biological sciences ever since. We postulate that protein conformational dynamics are also determined, at least in part, by amino acid sequence and that this relationship may be leveraged for construction of AI/ML models dedicated to predicting protein conformational ensembles. Accordingly, we describe a conceptual model architecture, which may be trained on sequence data in combination with conformationally sensitive structural information, coming primarily from nuclear magnetic resonance (NMR) spectroscopy. Notwithstanding certain limitations in this context, NMR offers abundant structural heterogeneity conducive to conformational ensemble prediction. As NMR and other data continue to accumulate, sequence-informed prediction of protein structural dynamics with AI/ML has the potential to emerge as a transformative capability across the biological sciences.

Artificial intelligence↗
DOE OSTI2022

Sensitivity analyses of a homogeneous model and a RZ model of the MYRRHA reactor in its critical configuration

Two homogenized models of the MYRRHA (Multi-purpose hybrid Research Reactor for High-tech Applications) reactor in its critical configuration are presented in this study. Both models will be verified by comparing the main reactor parameters (K{sub eff}, β{sub eff} and Λ) with those of the heterogeneous model and a sensitivity analysis will be performed. A sensitivity analysis of some important parameters related to reactivity, namely the vacuum coefficient, the Doppler and the power peaking factors, is also presented. The study of the vacuum coefficient has been carried out by analyzing two possible scenarios: 50% vacuum in the coolant (lead bismuth eutectic) and 100%, obtaining a list of the 10 reactions and nuclides that most affect the k{sub eff} value. With respect to the Doppler coefficient, it will be seen that a 300 degree increase in fuel temperature (starting at 800 K) results in a reduction of the total reactivity of the system by 134 pcm.. Finally, the map of the power peaking factors will be shown, as well as a sensitivity analysis. For making the sensitivity calculations Serpent-2 reactor physics Monte Carlo code has been used and JEFF-3.3 library has been chosen in order to continue with the OECD/NEA WPEC SG46 work evaluating the nuclear data of this library. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Non-nuclear Component Signatures for Warhead Dismantlement Confirmation

The verification of warhead dismantlement is expected to be an important component in future arms reduction treaties. Historic approaches developed with future arms control treaty verification in mind often involve intrusive measurements, process monitoring, and/or inspector presence to provide confidence that an authentic warhead has been dismantled. This work explores the possibility of reducing the negative impacts of these invasive approaches while also delivering a method that is more likely to provide non-sensitive data that can be shared with not only other nuclear weapons states but also non-nuclear weapons states partners. This work explores a novel approach for verifying dispositioned non-nuclear weapon components, providing confidence post-dismantlement that a treaty accountable item that was dismantled was in fact a treaty-relevant nuclear weapon system as declared. This method provides an alternative to intrusive inspection processes in nuclear weapons production environments, which would require significant changes to the host’s operational behaviors. It achieves this by identifying intrinsic neutron-induced signatures of non-nuclear components to determine their authenticity and estimate the duration they were exposed within a nuclear weapons system using technologies that are already in use for other national security applications. Intrinsic radiation effects studies are already a part of the stockpile aging and surveillance evaluations. However, none of these technologies and approaches have been previously considered for verification applications of non-nuclear component disposition. In this report, we introduce modeling studies that have been used to identify the most promising candidate parts and materials with signatures that are measurable and actionable. These models have been validated with laboratory measurements of signatures induced by the exposure of candidate materials to neutrons over a range of times. Predictive modeling then demonstrates the methodology for estimating exposure times and/or limits. Laboratory measurements of authentic non-nuclear parts from a dismantled warhead demonstrate the feasibility of employing these signature measurements. And finally, a concept of operations (CONOPS) for the potential use of this methodology is presented.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

Nuclear Data–Induced Uncertainties in Criticality Safety Analyses for High-Burnup and Extended Enrichment Fuels

Criticality safety analyses are conducted to show compliance with regulatory standards and to demonstrate safe operational conditions during the storage and transportation of spent nuclear fuel. Given the increased interest in the industry in low-enriched uranium plus (LEU+) and higher-burnup fuel, it is important to study the impact of such fuels’ use on criticality safety analyses and the resulting nuclear data–induced uncertainties. Here, in this work, nominal pressurized water reactor assemblies with LEU+ fuel enrichments up to 8 wt% 235 U and high burnups up to 80 GWd/tonne U were studied. The assemblies were placed in a generic burnup credit cask GBC-32. As a result of the different covariance libraries, using the ENDF/B-VII.1 nuclear data library consistently resulted in lower nuclear data uncertainties than did the use of the ENDF/B-VIII.0 data library. The highest contribution in the nuclear data–induced uncertainties resulted from the major actinides, and their contribution increased with increasing burnup and enrichment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

A refined assessment of nuclear data target accuracy requirements for ALFRED

The interest in target accuracy assessment has been recently renewed within the OECD/NEA Working Party on International Nuclear Data Evaluation Cooperation with an update exercise, thanks to the invaluable initiative of Massimo Salvatores. This work, moving from evaluations on the main core integral parameters of the Advanced Lead-cooled Fast Reactor European Demonstrator (ALFRED), and the identification of the associated target accuracies needed for improving its design, approaches the retrieval of target accuracy requirements for nuclear data, as the inverse problem of uncertainty quantification. The preliminary results obtained in a previous work are here refined by explicitly taking into account the total contribution due to correlations among variables in the optimization constraint, while its various components are evaluated individually. Moreover, three different sets of cost parameters are considered to introduce a bias in the solution in order to take in due account the relative difficulties in the execution of new differential experiments as needed for achieving the proposed target accuracies. By this, the obtained results are deemed usefully informative, and proposed for the update of a High Priority List which identifies the isotopes-reaction couples of most interest for future refinement experiments, especially when integrated with further analogous information collected on other advanced nuclear systems. Among the cross-sections whose refinement contributes the most to the reduction of the multiplication factor, the fission of Pu{sup 239} was found, which needs to be fixed below 1% in the range of interest for ALFRED (2 keV-4 MeV). Another contribution for the amelioration of the multiplication factor calculation accuracy, is due to the capture channel of Pu{sup 239}, for which the initial high uncertainty (around 15%) can be significantly reduced resorting to easily practicable experiments. The same occurs for the inelastic of Pb{sup 207}, for which the initial uncertainty value of around 50% can be drastically reduced up to target values between 4% and 7%.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Kinematic Imbalance Measurements with Pionless Events at MicroBooNE

MicroBooNE is an 89-ton liquid argon TPC in the Booster Neutrino Beam at Fermilab. This talk will present two recent measurements of kinematic imbalance in CC0pi events with single protons in the final state, using three years of MicroBooNE data. The two measurements focus on kinematic imbalance in the plane transverse to the neutrino beam, and a generalisation that extends the measurement in the longitudinal direction. These data are highly sensitive to the details of the nuclear ground state, and final state interactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Expert‐in‐the‐loop design of integral nuclear data experiments

Abstract Nuclear data are fundamental inputs to radiation transport codes used for reactor design and criticality safety. The design of experiments to reduce nuclear data uncertainty has been a challenge for many years, but advances in the sensitivity calculations of radiation transport codes within the last two decades have made optimal experimental design possible. The design of integral nuclear experiments poses numerous challenges not emphasized in classical optimal design, in particular, constrained design spaces (in both a statistical and engineering sense), severely under‐determined systems, and optimality uncertainty. We present a design pipeline to optimize critical experiments that uses constrained Bayesian optimization within an iterative expert‐in‐the‐loop framework. We show a successfully completed experiment campaign designed with this framework that involved two critical configurations and multiple measurements that targeted compensating errors in 239 Pu nuclear data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Sensitivity Studies, Gap Analysis, and Benchmark Experiment Optimization for Reactor Applications

In regards to nuclear data, some reactor applications may lack validation experiments, which reduces confidence in predicted results. This is especially true for emerging advanced reactor, micro reactor, and Accelerator Driven System (ADS) designs. This work presents an approach to design new criticality experiments that have similar k eff cross section sensitivities to an application of interest. This process involves simulations to generate cross-section sensitivities to a parameter of interest (such as k eff ), a gap analysis to determine which existing benchmarks are most similar to the application, and an experiment optimization. This work focuses on cross-section sensitives and gap analysis for three examples relevant to the reactor physics community including a Travelling Wave Reactor (TWR) type-design, Kilopower (a space reactor design), and a lead-bismuth eutectic cooled accelerator-driven system (ADS) to transmute minor actinides.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

IER 516 - Zirconium Test Assembly (ZTA) Preliminary Experimental Design [Slides]

Zirconium present in large quantities in criticality safety applications such as fuel manufacturing and processing facilities, and in commercial thermal nuclear reactors. ICSBEP lacks benchmarks optimized for zirconium sensitivity to validate zirconium evaluations. Evaluators lack isotopic differential nuclear data in regions of high importance to fission systems.

K-PSO 2.0↗
DOE OSTI2021

12 C(e,e'pN) measurements of short range correlations in the tensor-to-scalar interaction transition region

High-momentum configurations of nucleon pairs at short-distance are probed using measurements of the $^{12}$C$(e,e'p)$ and $^{12}$C$(e,e'pN)$ reactions (where $N$ is either $n$ or $p$), at high-$Q^2$ and $x_B>1.1$. The data span a missing-momentum range of 300--1000 MeV/c and are predominantly sensitive to the transition region of the strong nuclear interaction from a Tensor to Scalar interaction. The data are well reproduced by theoretical calculations using the Generalized Contact Formalism with both chiral and phenomenological nucleon-nucleon ($NN$) interaction models. This agreement suggests that the measured high missing-momentum protons up to $1000$ MeV/c predominantly belong to short-ranged correlated (SRC) pairs. The measured $^{12}$C$(e,e'pN)$ / $^{12}$C$(e,e'p)$ and $^{12}$C$(e,e'pp)$ / $^{12}$C$(e,e'pn)$ cross-section ratios are consistent with a decrease in the fraction of proton-neutron SRC pairs and increase in the fraction of proton-proton SRC pairs with increasing missing momentum. This confirms the transition from an isospin-dependent tensor $NN$ interaction at $\sim 400$ MeV/c to an isospin-independent scalar interaction at high-momentum around $\sim 800$ MeV/c as predicted by theoretical calculation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Nuclear data uncertainty propagation applied to the versatile test reactor conceptual design

We report the Versatile Test Reactor (VTR) currently under development is a 300 MWth sodium-cooled fast reactor (SFR) fueled with ternary metal alloy fuel, which aims to accelerate the testing of advanced nuclear fuels, materials, instrumentation, and sensors in high flux environments that are necessary to license the next generation of advanced reactor concepts. To support the VTR design process, uncertainties associated with the nuclear data has been propagated through the reactor core neutronics calculation to global parameters of interest, such as the core multiplication factor, kinetic parameters, and various reactivity feedback coefficients, following the sensitivity based uncertainty propagation approach. By folding the sensitivity coefficients, separately computed by the generalized perturbation theory code PERSENT and Monte Carlo code Serpent 2, with the variance-covariance matrices from COMMARA-2.0, we obtain the reaction-wise, isotope-wise, and overall uncertainties for each response of interest due to nuclear data uncertainty. With Serpent 2, the statistical error of the uncertainty is obtained by propagating the statistical error of the sensitivity coefficients through the same process using a newly developed uncertainty propagation method. From both codes, the overall top uncertainty contributors are found to be the cross section of Fe-56 elastic scattering, Na-23 elastic scattering, and U 238 inelastic scattering. The large contributions of the Fe-56 elastic scattering cross sections to global parameters are due to its relatively large relative uncertainty of 5–10% in nuclear data and the large volume of Fe-containing reflector assemblies in the fairly compact VTR core design. Both codes agreed well for the overall uncertainty estimates of all responses of interest, except the delayed neutron fraction, prompt neutron generation time, and the coolant density feedback coefficient, where Serpent 2 yielded a much larger value than PERSENT due to the large statistical error of sensitivity coefficients. The calculated uncertainties are also compared to those associated with other SFR cores. Another outcome of this study is a variance-covariance matrix of reactivity coefficients, which can be used in the subsequent uncertainty propagation to the system level to investigate the impact of identified uncertainties on system responses in the safety analysis.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Status of the CERBERUS Evaluation for the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook

Modeling & Simulation (M&S) tools are used to analyze advanced reactor designs and the safety of current nuclear operations. As computers continue to improve, we are able to enhance resolution in our calculations. Therefore, the limitations of simulation capability are in the quality of data that is being used, including our ability to quantify the uncertainty and sensitivity of that data. In order to model systems of interest with increasing accuracy, the industry must improve key nuclear data measurements. The International Criticality Safety Benchmark Evaluation Project (ICSBEP) compiles and evaluates experiment data in a handbook that can be used by criticality safety engineers and others to validate computer codes and cross section libraries at nuclear facilities. Both critical and subcritical experiments are included in the handbook. These experiments, along with differential measurements, can help improve the quality of nuclear data. Concerns regarding the accuracy of Cu nuclear data have been published. The large values and trend of C-E for the Zeus intermediate energy benchmark, being one of the primary examples. Furthermore, very few experiments have been designed to be sensitive to Cu (as shown in Figure 1), so an integral, critical experiment is needed to help resolve these differences.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Nuclear Data Impact Assessment for the HTR-10 Pebble-Bed Reactor Using SCALE

The HTR-10 was used as a representative pebble-bed high-temperature gas-cooled reactor in this assessment of nuclear data’s impact on important reactor and spent fuel metrics, including safety-related quantities such as the effective multiplication factor (k eff ), temperature reactivity feedback, spent fuel inventory, and decay heat. Using the SCALE code system tools and ENDF/B-VII.1 nuclear data libraries, we quantify the effect of nuclear data uncertainties on these key performance metrics for both fresh fuel and equilibrium core configurations. For reactor core key parameters, important contributors to uncertainty include reactions of 235 U [$\bar{v}$, fission, (n, γ)], 238 U [elastic, (n, γ)], and graphite [elastic, (n, γ)]. Additional important contributors for the equilibrium core include reactions of higher actinides ( 239 Pu, 240 Pu) and fission products ( 135 Xe, 149 Sm). For spent fuel analysis, most nuclide inventory uncertainties remain below 5%. Higher uncertainties up to 11% are being observed for minor actinides like 243 Am and 244 Cm. Additionally, fission product uncertainties in 155 Eu and 155 Gd, of 25% and 23% respectively, are also significant and have implications for burnup credit applications. 110m Ag also shows high uncertainty of up to 11%, mainly due to fission product yield uncertainties. Decay heat relative uncertainties remain below 0.6% up to 10 years’ cooling time after fuel discharge. The highest relative uncertainty of 1.5% occurs at 500 years of cooling; however, because the decay heat value is very low at that time, the absolute uncertainty is not significant. This work demonstrates that extending assessments beyond fresh fuel k eff to include irradiated cores, nuclide inventories, and decay heat is essential in understanding the behavior of uncertainties as a function of fuel burnup and can support improvements of safety margins and spent fuel management.

Nuclear data impact↗